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Adaptive nowcasting of influenza outbreaks using Google searches
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Preis, Tobias and Moat, Helen Susannah (2014) Adaptive nowcasting of influenza outbreaks using Google searches. Royal Society Open Science , Volume 1 (Number 2). Article number 140095. doi:10.1098/rsos.140095 ISSN 2054-5703.
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Official URL: http://dx.doi.org/10.1098/rsos.140095
Abstract
Seasonal influenza outbreaks and pandemics of new strains of the influenza virus affect humans around the globe. However, traditional systems for measuring the spread of flu infections deliver results with one or two weeks delay. Recent research suggests that data on queries made to the search engine Google can be used to address this problem, providing real-time estimates of levels of influenza-like illness in a population. Others have however argued that equally good estimates of current flu levels can be forecast using historic flu measurements. Here, we build dynamic ‘nowcasting’ models; in other words, forecasting models that estimate current levels of influenza, before the release of official data one week later. We find that when using Google Flu Trends data in combination with historic flu levels, the mean absolute error (MAE) of in-sample ‘nowcasts’ can be significantly reduced by 14.4%, compared with a baseline model that uses historic data on flu levels only. We further demonstrate that the MAE of out-of-sample nowcasts can also be significantly reduced by between 16.0% and 52.7%, depending on the length of the sliding training interval. We conclude that, using adaptive models, Google Flu Trends data can indeed be used to improve real-time influenza monitoring, even when official reports of flu infections are available with only one week's delay.
| Item Type: | Journal Article | ||||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software R Medicine > RC Internal medicine Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science |
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| Divisions: | Faculty of Social Sciences > Warwick Business School > Behavioural Science Faculty of Social Sciences > Warwick Business School |
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| Library of Congress Subject Headings (LCSH): | Influenza -- Data processing, Data mining, Web search engines, Automatic abstracting, Influenza -- Computer network resources | ||||||||
| Journal or Publication Title: | Royal Society Open Science | ||||||||
| Publisher: | The Royal Society Publishing | ||||||||
| ISSN: | 2054-5703 | ||||||||
| Official Date: | 10 October 2014 | ||||||||
| Dates: |
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| Volume: | Volume 1 | ||||||||
| Number: | Number 2 | ||||||||
| Article Number: | Article number 140095 | ||||||||
| DOI: | 10.1098/rsos.140095 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Date of first compliant deposit: | 26 February 2016 | ||||||||
| Date of first compliant Open Access: | 26 February 2016 | ||||||||
| Funder: | Research Councils UK (RCUK) | ||||||||
| Grant number: | EP/K039830/1 |
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